Results 121 to 130 of about 6,194,626 (351)
Advanced Functional Materials, EarlyView.An ultra‐robust memristor based on SrTiO3‐CeO2 (S‐C) vertically aligned nanocomposite (VAN) achieving exceptional endurance of 1012 switching cycles via interface engineering. Artificial neural networks (ANNs) integrated with S‐C VAN memristors exhibit high training accuracy across multiple datasets.
Zedong Hu +12 more
wiley +1 more source
The maximum flow in dynamic networks [PDF]
Computer Science Journal of Moldova, 2005 The dynamic maximum flow problem that generalizes the static maximum flow problem is formulated and studied. We consider the problem on a network with capacities depending on time, fixed transit times on the arcs, and a given time horizon.
Maria A. Fonoberova, Dmitrii D. Lozovanu
doaj
Mathematical evaluation of two parameter flow cytometric histograms [PDF]
, 1981 Karl‐U. Scholz
openalex +1 more source
Design and Applications of Multi‐Frequency Programmable Metamaterials for Adaptive Stealth
Advanced Functional Materials, EarlyView.This article provides a comprehensive overview of metamaterials, including their fundamental principles, properties, synthesis techniques, and applications in stealth, as well as their challenges and future prospects. It covers topics that are more advanced than those typically discussed in existing review articles, while still being closely connected ...
Jonathan Tersur Orasugh +4 more
wiley +1 more source
Mathematical model of hydrate formation in the flow of moist gas in tubes [PDF]
, 1984 V. M. Bilyushov
openalex +1 more source
Amorphous High Entropy Alloy Nanosheets Enabling Robust Li–S Batteries
Advanced Functional Materials, EarlyView.Amorphous ultrathin FeCoNiMoW high entropy alloy nanosheets are incorporated into the polypropylene separator of lithium‐sulfur batteries, enhancing their capacity, rate performance, and cycling stability. Abstract High‐entropy alloys (HEAs) show great potential for catalyzing complex multi‐step reactions, but optimizing their parameters, i.e ...
Ren He +20 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Separation by Electrosorption of Organic Compounds in a Flow‐Through Porous Electrode: I . Mathematical Model for One‐Dimensional Geometry [PDF]
, 1983 Richard C. Alkire, Ronald S. Eisinger
openalex +1 more source
Advanced Functional Materials, EarlyView.Integrating polyethyleneimine and carbon black into polyurethane enhances electron transport and mechanical durability. The resulting sensor achieves significantly improved electrical signal and sensitivity, enabling efficient machine learning‐based tactile signal recognition in bionic applications.
Xiangkun Bo +4 more
wiley +1 more source
Maximal Flow Through a Network
Canadian Journal of Mathematics - Journal Canadien de Mathematiques, 1956 JR L. R. FORD, D. R. Fulkerson
semanticscholar +1 more source